Industries

Our predictive insights at work

What we enable you to do

Insights for the real world
Overcome time and computational hurdles

Overcome time and computational hurdles

Predictive models are all the rage. But in the real world, creating them is hard. Ever more time and computing horsepower are needed, as the complexity of the relationships within big data grows. We overcome those hurdles with our machine-learning technology. Plus, we need not make any a priori assumptions about the relationships within raw data. We build them by exploring all possible models to find the best fit.

Transcend missing data

Transcend missing data

Billions of sensors and devices have created a massive gusher of data. But in the real world that data is often disconnected and sometimes missing. Gaps in data can throw a wrench into even the most powerful statistical methods. Heavy lifting needs to be done to transcend those gaps. Fortunately, we have unique technology that can do just that. No need to worry, power on.

Make quantifiable decisions

Make quantifiable decisions

Decisions may never be easy. But we can make them easier. Consider a telecom provider; it must decide how to balance advertising to all those likely to buy its services against reducing its ad spend on all those unlikely to buy. Similar resource-allocation decisions must be made in healthcare and financial services every day. With our insights, you will know precisely what that tradeoff is, so that you can make quantifiable decisions. Why settle for reality when you can improve on it.

Why we are unique

Insights are not made equal
  1. Better than Data Visualization

    Masquerade Modeling

    What is it: Data visualization sometimes masquerades as predictive modeling. What it really does is display your data in such a way that you can identify what you want.

    The problem: You must act as the predictive model. Unless you already know precisely what you want to identify, data visualization cannot create predictive insights. We can do better.

  2. Better than Ready-Made Modeling

    Cookie-Cutter Modeling

    What is it: Ready-made modeling tries to create predictive insights from cookie-cutter models that are built around pre-selected data attributes.

    The problem: Unless the attributes of your data precisely match those on which the cookie-cutter models were built, their predictive power rapidly deteriorates. We can do better.

  3. Better than Human Modeling

    Snapshot Modeling

    What is it: Statisticians are often used to create predictive insights, but a reliance on them produces models that are snapshots in time.

    The problem: As the number of data attributes grows, the number of relationships among them grows even faster. Ultimately there is a limit to how many attributes that even the best statisticians can handle, especially when confronted with big data flows. Plus, if your data’s underlying relationships frequently change, as those based on human behavior do, models quickly become outdated. Keeping them up-to-date requires an army of analysts. We can do better.

  4. Better than Machine-Learned Modeling

    Idealized Modeling

    What is it: Machine-learning technology is sometimes used to reduce the reliance on human modeling, but it often requires idealized datasets – datasets that are highly structured or have well-defined outcomes.

    The problem: Idealized datasets are rare in the real world. Even then, nearly all machine-learning technology needs some human assumptions before it can start modeling. Ironically, that diminishes the value of using such technology to create predictive insights. We can do better.

  5. We Are DecisionQ

    DecisionQ

    We combine analytic skill, statistical methods, and unique machine-learning technology to create our predictive insights. We do not need to make assumptions about the relationships within raw data beforehand. That removes human bias. The relationships (or interdependencies, in statistics lingo) are built entirely from raw data by exploring the predictive power of each possible model to find the best fit. No need for armies of analysts or stacks of servers every time predictive insights are sought.

We deliver on the promise of predictive analytics

We deliver on the promise of predictive analytics

Predictive analytics has become cliché. Some even claim that guesswork based on data visualization is predictive. But real predictive analytics reveals the relationships within raw data to deliver insights. That is what we do. We produce highly personalized predictions. That is the difference between speculation on what part of a population might have an illness and a smart prediction of whether you might have it. Which is more valuable?

We combine tested methods with unique technology

We combine tested methods with unique technology

We create our predictive models through the combination of analytic skill, statistical methods, and unique machine-learning technology. That allows us to reveal the hidden relationships within raw data, making our insights more precise. Even after our models are deployed, they can be dynamically reconfigured as new data arrives. That keeps them up-to-date. Bottom line: more powerful insights, faster, and at lower cost.

Our business model is our models

Our business model is our models

At the heart of everything we do are our models. Our models are what produce the insights that our partners prize. With those insights, they can lower operating costs, reduce risk, and achieve more rapid growth. We share in those benefits. That is how we grow together.

Careers

What will you make with DecisionQ?
Be a creator

Be a creator

Whether you are a recent graduate or an experienced professional, DecisionQ may be the place for you. Here you will become an integral part of our team and be relied upon to create results that help not only our partners excel at what they do, but also our company grow. You can be part of DecisionQ’s legacy of creating unparalleled insights for partners around the world.

Work with the best and brightest

Work with the best and brightest

If you are interested in being a part of our team – people who want to create insights and cultivate their skills – then this is the place for you. We seek those who want to devote their careers to thinking about the science of statistics and how it impacts our lives and society. Working in such an environment requires a culture of learning and collaboration. That means our analysts need to work together, not simply to share insights, but to create new intellectual capital.

Build the career you want

Build the career you want

A wonderful feature of being part of a growing company is that you have room to run. New opportunities will enable you to stretch your skills and explore new fields. As you help the industries we serve grow, you will grow with them. You can build your skills and showcase your potential while working on some of the private and public sectors’ most pressing issues.